Almost Everything You Wanted to Know About
Making Tables and Figures
Definitions | Getting Organized
| Referencing from Text | Abbreviation
of "Fig." | Numbering
Figures and Tables |
| Placement in paper | Legends
| Legend Postion | Anatomy
of a table | Anatomy of a graph |
| Compound Figures | Bar
Graphs | Frequency Histograms |
Scatterplots | Line
Once your statistical
analyses are complete, you will need to summarize the data and
results for presentation to your readers. Data summaries may
take one of 3 forms: text, Tables and Figures.
contrary to what you may have heard, not all analyses or results
warrant a Table or Figure. Some simple results are best stated
in a single sentence, with data summarized parenthetically:
Seed production was higher
for plants in the full-sun treatment (52.3 +/-6.8 seeds) than
for those receiving filtered light (14.7+/- 3.2 seeds, t=11.8,
Tables present lists of numbers or text in columns, each column
having a title or label. Do not use a table when you wish to
show a trend or a pattern of relationship between sets of values
- these are better presented in a Figure. For instance, if you
needed to present population sizes and sex ratios for your study
organism at a series of sites, and you planned to focus on the
differences among individual sites according to (say) habitat
type, you would use a table. However, if you wanted to show us
that sex ratio was related to population size, you would
use a Figure.
Figures are visual presentations of results, including graphs,
diagrams, photos, drawings, schematics, maps, etc. Graphs are
the most common type of figure and will be discussed in detail;
examples of other types of figures are included at the end of
this section. Graphs show trends or patterns of relationship.
Organizing your presentation: Once you have done your analyses and decided
how best to present each one, think about how you will arrange
them. Your analyses should tell a "story" which leads
the reader through the steps needed to logically answer the question(s)
you posed in your Introduction. The order in which you present
your results can be as important in convincing your readers as
what you actually say in the text.
How to refer to Tables and Figures
from the text: Every Figure
and Table included in the paper MUST be referred to from the
text. Use sentences that draw the reader's attention to the relationship
or trend you wish to highlight, referring to the appropriate
Figure or Table only parenthetically:
Germination rates were
significantly higher after 24 h in running water than in controls
DNA sequence homologies
for the purple gene from the four congeners (Table 1)
show high similarity, differing by at most 4 base pairs.
sentences that give no information other than directing the reader
to the Figure or Table:
Table 1 shows the summary
results for male and female heights at Bates College.
How to number Tables and Figures: Figures and Tables are numbered independently,
in the sequence in which you refer to them in the text,
starting with Figure 1 and Table 1. If, in revison, you change
the presentation sequence of the figures and tables, you must
renumber them to reflect the new sequence.
Placement of Figures and Tables within
the Paper: In manuscripts (e.g.
lab papers, drafts), Tables and Figures are usually put on separate
pages from text material. In consideration of your readers, place
each Table or Figure as near as possible to the place where you
first refer to it (e.g., the next page). It is permissable to
place all the illustrative material at the end of the Results
section so as to avoid interrupting the flow of text. The Figures
and Tables may be embedded in the text, but avoid breaking up
the text into small blocks; it is better to have whole pages
of text with Figures and Tables on their own pages.
The "Acid Test" for Tables
and Figures: Any Table or Figure
you present must be sufficiently clear, well-labeled, and described
by its legend to be understood by your intended audience without
reading the results section, i.e., it must be able to stand alone
and be interpretable. Overly complicated Figures or Tables may
be difficult to understand in or out of context, so strive for
simplicity whenever possible. If you are unsure whether your
tables or figures meet these criteria, give them to a fellow
biology major (not in your course) and ask them to interpret
Descriptive Legends or Captions: To pass the "acid test" above, a clear
and complete legend (sometimes called a caption) is essential.
Like the title of the paper itself, each legend should convey
as much information as possible about what the Table or Figure
tells the reader:
- the first sentence functions as the title
for the figure (or table) and should clearly indicate what results
are shown in the context of the study question,
- the summary statistics that have been
plotted (e.g., mean and SEM),
- the organism studied in the experiment
- context for the results: the treatment
applied or the relationship displayed, etc.
- location (ONLY if a field experiment),
- specific explanatory information needed
to interpret the results shown (in tables, this is frequently
done as footnotes) and may include a key to any annotations,
- culture parameters or conditions if applicable
(temperature, media, etc) as applicable, and,
- sample sizes and statistical test summaries
as they apply.
- Do not simply restate the axis labels
with a "versus" written in between.
Figure 1. Height frequency
(%) of White Pines (Pinus strobus) in the Thorncrag Bird
Sanctuary, Lewiston, Maine, before and after the Ice Storm of
'98. Before, n=137, after, n=133. Four trees fell during the
storm and were excluded from the post-storm survey.
In the examples later in this section,
note the completeness of the legends. When you are starting out,
you can use one of these examples (or an appropriate example
from a published paper) as a model to follow in constructing
your own legends.
Questions frequently arise about how much methodology to include
in the legend, and how much results reporting should be done.
For lab reports, specific results should be reported in the results
text with a reference to the applicable Table or Figure. Other
than culture conditions, methods are similarly confined to the
The reality: How much methodology and results are reported
in the legends is journal specific. Hot-off-the-press journals
like Science and Nature so limit the body text
that virtually all of the Methods are presented in the Figure
and Table legends or in footnotes. Much of the results are also
reported in the legends.
Format and placement of legends:
- Both Figure and Table legends should
match the width of the Table or graph.
- Table legends
go above the body of the Table and are left justified;
Tables are read from the top down.
- Figure legends
go below the graph and are left justified; graphs and
other types of Figures are usually read from the bottom up.
- Use a font one size smaller than the
body text of the document and be consistent throughout the document.
- Use the same font as the body text.
The Anatomy of a Table
Table 4 below shows the typical layout
of a table in three sections demarcated by lines. Tables are
most easily constructed using your word processor's table function
or a spread sheet such as Excel. Gridlines or boxes, commonly
invoked by word processors, are helpful for setting cell and
column alignments, but should be eliminated from the printed
version. Tables formatted with cell boundaries showing are unlikely
to be permitted in a journal.
Example 1: Courtesy of Shelley
Example 2: Courtesy of Shelley Ball.
Example 3: Courtesy of Greg Anderson
In these examples notice several things:
- the presence of a period after
- the legend (sometimes called the caption)
goes above the Table;
are specified in column headings wherever appropriate;
- lines of demarcation are used to set
legend, headers, data, and footnotes apart from one another.
are used to clarify points in the table, or to convey repetitive
information about entries;
- footnotes may also be used to denote
statistical differences among groups.
The Anatomy of a Figure
The sections below show when and how to
use the four most common Figure types (bar graph, frequency histogram,
XY scatterplot, XY line graph.) The final section gives examples
of other, less common, types of Figures.
Parts of a Graph: Below are example figures (typical line and bar
graphs) with the various component parts labeled in red. Refer
back to these examples if you encounter an unfamiliar term as
you read the following sections.
Some general considerations about Figures:
- Big or little?
For course-related papers, a good rule of thumb is to size your
figures to fill about one-half of a page. Use an easily readable
font size for axes and ticks. Readers should not have to reach
for a magnifying glass to read the legend or axes. Compound
figures may require a full page.
- Color or no color? Most often black and white is preferred. The
rationale is that if you need to photocopy or fax your paper,
any information conveyed by colors will be lost to the reader.
However, for a poster presentation or a talk with projected images,
color can be helpful in distinguishing different data sets. Every
aspect of your Figure should convey information; never use
color simply because it is pretty.
- Title or no title? Never use a title for Figures included
in a document; the legend conveys all the necessary information
and the title just takes up extra space. However, for posters
or projected images, where people may have a harder time
reading the small print of a legend, a larger font title is very
- Offset axes or not? Elect to offset the axes only when data points
will be obscured by being printed over the Y axis.
- Error bars or not? Always include error bars (e.g., SD or SEM)
when plotting means. In some courses you may be asked to plot
other measures associated with the mean, such as confidence intervals.
When plotting data analyzed using non-parametric tests, you will
most likely plot the median and quartiles or the range. These
might be dotplots or box and whisker plots.
- Tick marks -
Use common sense when deciding on major (numbered) versus minor
ticks. Major ticks should be used to reasonably break up the
range of values plotted into integer values. Within the major
intervals, it is usually necessary to add minor interval ticks
that further subdivide the scale into logical units (i.e.,
a interval that is a factor of the major tick interval). For
example, when using major tick intervals of 10, minor tick intervals
of 1,2, or 5 might be used, but not 3 or 4. When the data follow
a uniform interval on the x-axis (e.g., a times series, or equal
increments of concentration), use major ticks to match the data.
No minor intervals would be used in this case.
width- The width of the figure legend should match the
width of the graph (or other content.
- Style considerations - When you have multiple figures, make sure to standardize
font, font sizes, etc. such that all figures look stylistically
When you have multiple graphs, or graphs
and others illustrative materials that are interrelated, it may
be most efficient to present them as a compound figure. Compound
figures combine multiple graphs into one common figure and share
a common legend. Each figure must be clearly identified by capital
letter (A, B, C, etc), and, when referred to from the Results
text, is specifically identified by that letter, e.g., "...(Fig. 1b)". The legend of the compound figure must also
identify each graph and the data it presents by letter.
Four Common Figure Types
Bar graphs are used when you wish to compare
the value of a single variable (usually a summary value such
as a mean) among several groups. For example, a bar graph is
appropriate to show the mean sizes of plants harvested from plots
that received 4 different fertilizer treatments. (Note that although
a bar graph might be used to show differences between only 2
groups, especially for pedagogical purposes, editors of many
journals would prefer that you save space by presenting such
information in the text.)
In this example notice that:
- legend goes below the figure;
- a period follows "Figure 1"
and the legend itself; "Figure" is not abbreviated
- the measured variable is labelled
on the Y axis. In most cases units are given here as well (see
- the categorical variable (habitat)
is labelled on the X axis, and each category is designated;
- a second categorical variable
(year) within habitat has been designated by different bar
fill color. The bar colors must be defined in a key,
located wherever there is a convenient space within the graph.
- error bars are included, extending +1
SD or SEM above the mean.
- statistical differences may be indicated
by a system of letters above the bars, with an accompanying note
in the caption indicating the test and the significance level
- the completeness of the legend, which
in this case requires over 3 lines just to describe the treatments
used and variable measured.
- axis labels, with units;
- treatment group (pH) levels specified
on X axis;
- error bars and group sample sizes accompany
each bar, and each of these is well-defined in legend;
- statistical differences in this case
are indicated by lines drawn over the bars, and the statistical
test and significance level are identified in the legend.
Frequency histograms (also called frequency
distributions) are bar-type graphs that show how the measured
individuals are distributed along an axis of the measured variable.
Frequency (the Y axis) can be absolute (i.e. number of
counts) or relative (i.e. percent or proportion of the
sample.) A familiar example would be a histogram of exam scores,
showing the number of students who achieved each possible score.
Frequency histograms are important in describing populations,
e.g. size and age distributions.
Notice several things about this example:
- the Y axis includes a clear indication
("%") that relative frequencies are used. (Some examples
of an absolute frequencies: "Number of stems", "Number
of birds observed")
- the measured variable (X axis) has been
divided into categories ("bins") of appropriate width
to visualize the population distribution. In this case, bins
of 0.2 cm broke the population into 7 columns of varying heights.
Setting the bin size at 0.5 cm would have yielded only 3 columns,
not enough to visualize a pattern. Conversely, setting the bin
size too small (0.05 cm) would have yielded very short columns
scattered along a long axis, again obscuring the pattern.
- the values labeled on the X axis are
the bin centers;
- sample size is clearly indicated, either
in the legend or (in this case) the graph itself;
- the Y axis includes numbered and minor
ticks to allow easy determination of bar values.
These are plots of X,Y coordinates showing
each individual's or sample's score on two variables.
When plotting data this way we are usually interested in knowing
whether the two variables show a "relationship", i.e.
do they change in value together in a consistent way?
Note in this example that:
- each axis is labeled (including units
where appropriate) and includes numbered and minor ticks to allow
easy determination of the values of plotted points;
- sample size is included in the legend
or the body of the graph;
- if the data have been analyzed statistically
and a relationship between the variables exists, it may be indicated
by plotting the regression line on the graph, and by giving the
equation of the regression and its statistical significance in
the legend or body of the figure;
- the range of each axis has been carefully
selected to maximize the spread of the points and to minimize
wasted blank space where no points fall. For instance, the X
axis is truncated below 50 g because no plants smaller than 52
g were measured. The ranges selected also result in labeled ticks
that are easy to read (50, 100, 150
, rather than 48, 96,
Which variable goes on the X axis?
When one variable is clearly dependent
upon another (e.g. height depends on age, but it is hard to imagine
age depending on height), the convention is to plot the dependent
variable on the Y axis and the independent variable on
the X axis. Sometimes there is no clear independent variable
(e.g. length vs. width of leaves: does width depend on width,
or vice-versa?) In these cases it makes no difference which variable
is on which axis; the variables are inter-dependent, and
an X,Y plot of these shows the relationship BETWEEN them
(rather than the effect of one upon the other.)
In the example plotted above, we can imagine
that seed production might depend on plant biomass, but
it is hard to see how biomass could depend directly on seed production,
so we choose biomass as the X axis. Alternatively, the relationship
might be indirect: both seed production and plant
biomass might depend on some other, unmeasured variable. Our
choice of axes to demonstrate correlation does not necessarily
X,Y Line Graph
Line graphs plot a series of related values
that depict a change in Y as a function of X. Two common examples
are a growth curve for an individual or population over time,
and a dose-response curve showing effects of increasing doses
of a drug or treatment.
When to connect the dots? If each point in the series is obtained from
the same source and is dependent on the previous values (e.g.
a plot of a baby's weight over the course of a year, or of muscle
strength on successive contractions as a muscle fatigues), then
the points should be connected by a line in a dot-to-dot fashion.
If, however, the series represents independent measurements of
a variable to show a trend (e.g. mean price of computer memory
over time; a standard curve of optical density vs. solute concentration),
then the trend or relationship can be modeled by calculating
the best-fit line or curve by regression analysis (see A
Painless Guide to Statistics ) Do not connect the
dots when the measurements were made independently.
In this example notice:
- a different symbol is
used for each group (species), and the key to the symbols is
placed in the body of the graph where space permits. Symbols
are large enough to be easily recognizable in the final graph
- each point represents
a mean value, and this is stated in the legend. Error bars are
therefore plotted for each point and defined in the legend as
- because measurements
were taken on independent groups for each species, the points
are NOT connected dot-to-dot; instead a curve is fitted to the
data to show the trend.
Notice here that:
- this time the dots ARE connected dot-to-dot
within each treatment, because cumulative percent germination
was measured within the same set of seeds each day, and thus
is dependent on the measurements of the prior days;
- a different symbol is used for each treatment,
and symbols are large enough (and connecting lines fine enough)
so that all can be easily read at the final graph size;
- in addition to the key to symbols, two
other kinds of helpful information are supplied in the body of
the figure: the values of the highest and lowest final cumulative
percents, and a dashed line (baseline) showing the lowest cumulative
% germination achieved. This baseline is defined in the legend.
Some Other Types of Figures
Figure 9. Aerial photo
of the study site ca. 1949 and in 1998 (inset) showing the regeneration
of the forest. Photos courtesy of the USDA Field Office, Auburn,
Notice here that:
- A photograph is a figure.
- Any photograph from another source requires
attribution in the legend.
- Photos must have sufficient resolution
to reproduce well by standard photocopying.
Source: Lawson et. al, 1999.
J.Biol. Chem. 274(14):9871-9980. Used by permission of the authors.
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